code: def shared_fc_layers(self):
      return [
          self.blocks[i].fc_layer for i in range(self.num_shared_blocks)
      ]
  
imports: from typing import List, Optional, Tuple
  import torch
  import torch.nn
  from ludwig.modules.normalization_modules import GhostBatchNormalization
  from ludwig.utils.entmax import Entmax15, EntmaxBisect, Sparsemax
  from ludwig.utils.torch_utils import LudwigModule
label_desc: Use image node_id 3 for calling the FeatureTransformer obj's underlying member method code with example usage: obj.shared_fc_layers() and returns: unknown